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org.apache.spark.SparkException: Exiting due to error from cluster
scheduler: All masters are unresponsive! Giving up.
at org.apache.spark.scheduler.TaskSchedulerImpl.error(
TaskSchedulerImpl.scala:438)
at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.dead(
SparkDeploySchedulerBackend.scala:124)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint.markDead(
AppClient.scala:264)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2$$
anonfun$run$1.apply$mcV$sp(AppClient.scala:134)

org.apache.spark.SparkException: Exiting due to error from cluster
scheduler: All masters are unresponsive! Giving up.
at org.apache.spark.scheduler.TaskSchedulerImpl.error(
TaskSchedulerImpl.scala:438)
at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.dead(
SparkDeploySchedulerBackend.scala:124)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint.markDead(
AppClient.scala:264)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2$$
anonfun$run$1.apply$mcV$sp(AppClient.scala:134)

Root Cause Analysis

org.apache.spark.SparkException

Exiting due to error from cluster
scheduler: All masters are unresponsive! Giving up.
at org.apache.spark.scheduler.TaskSchedulerImpl.error(
TaskSchedulerImpl.scala:438)
at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.dead(
SparkDeploySchedulerBackend.scala:124)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint.markDead(
AppClient.scala:264)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2$$
anonfun$run$1.apply$mcV$sp(AppClient.scala:134)